ABSTRACT
Optimum research on famous TCM doctors’ experienced prescriptions can optimize the composition of prescriptions which originated from experienced prescriptions, clarify the functions of indications and efficacy features of experienced prescriptions. Case report forms which are normally adapted to clinical new medicine study cannot meet the demand of observational study to optimize experienced prescriptions. This article expounded design features, structure elements and collection timing and proposed requirements for information collection through practice of case report forms in the optimum research on famous TCM doctors’ experienced prescriptions, with a purpose to realize the optimization of experienced prescriptions through observational study on famous TCM doctors’ experienced prescriptions and provide evidence for further clinical research on experienced prescriptions.
ABSTRACT
Based on traditional Chinese medicine (TCM) herb data of inpatient department and senior famous TCM doctors from many TCM hospitals in China. Existing problems of TCM herb data standardization preprocessing were analyzed in order to explore scientific and reasonable preprocessing program which can provide technical support for the accurate analysis of herbal information. Clinical medicine doctors and herbal pharmacists collaborated and analyzed the real-world TCM herb data collected from multi-regions. In connection with characteristics of TCM, data mining was combined in the analysis of requirement to identify existing problems and explore appropriate problem-solving solutions. The results showed that based on the Pharmacopoeia of the People's Republic of China (PPRC, 2010 version) and regional herb preparing and dispensing guidelines, the herb collection rules, methods and processes were made for the herb data standardization. Herbal data processing program for different regions were formulated. It was concluded that herb data standardization rules and methods made by this plan solved standardization and accuracy of TCM herb data analysis and utilization in multi-area.